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A cross-disciplinary and severity-based study of author-related reasons for retraction.

Shaoxiong Brian XuGuangwei Hu
Published in: Accountability in research (2021)
Previous research has found authors of retracted publications responsible for the vast majority of retractions. Although considerable research attention has been given to reasons for retraction, few studies have examined author-related reasons from a cross-disciplinary and a severity-based perspective. Drawing on data from the Web of Science Core Collection, this study examined 6,861 retraction notices published before 2020, in which authors were identified as the sole entities responsible for retraction. A close scrutiny identified 17 distinct reasons for retraction, with the three most frequent (i.e., plagiarism/self-plagiarism, unreliable data/findings, and data fabrication/falsification) accounting for 78.87% of the retraction notices. Based on the severity of the culpable actions involved, the 17 reasons were grouped into five categories: blatant misconduct (disclosed in 61.08% of the retraction notices), inappropriate conduct (18.18%), questionable conduct (0.95%), honest error (4.62%), and uncategorizable conduct (30.52%). Retraction notices in hard disciplines (i.e., natural sciences) were found more likely than those in soft disciplines (i.e., social sciences, arts, and the humanities) to disclose authorship issues, unreliable data/findings, uncategorizable conduct, and inappropriate conduct. Retraction notices in soft disciplines were more likely than those in hard disciplines to disclose unspecified misconduct and blatant misconduct.
Keyphrases
  • electronic health record
  • big data
  • randomized controlled trial
  • mental health
  • data analysis
  • deep learning